Our Services
We provide a wide range of data annotation services to power your most demanding AI and machine learning projects.
Our globally distributed team of expert annotators ensures cultural diversity and robust bias control, delivering nuanced and impartial data for a more equitable AI.
Image Annotation
High-precision image annotation for computer vision models.
- Bounding Boxes: Accurate object detection with rectangular boxes.
- Polygonal Segmentation: Detailed object outlines for irregular shapes.
- Semantic Segmentation: Pixel-level classification for scene understanding.
- Keypoint Annotation: Identifying key points for pose estimation and facial recognition.
Expert Video Annotation
Industry-leading video annotation for complex dynamic scenarios, providing the nuanced data needed for sophisticated action recognition and object tracking models.
- Object Tracking: Consistent object identification and tracking across thousands of frames.
- Event Detection: Precise tagging of complex events and multi-object interactions.
- Temporal Annotation: Labeling sequences of actions over time for comprehensive behavior analysis.
Text Annotation
Enriching textual data for natural language processing.
- Named Entity Recognition (NER): Identifying and categorizing entities like names, places, and organizations.
- Sentiment Analysis: Determining the emotional tone of text.
- Text Classification: Categorizing text into predefined topics or genres.
Multilingual Audio Generation & Annotation
Generating and labeling audio data across multiple languages for advanced speech technologies.
- Text-to-Speech (TTS) Generation: Creating high-quality, natural-sounding audio in various languages.
- Audio Transcription: Accurate conversion of speech to text.
- Sound Event Detection: Identifying and labeling specific sounds within audio files.
- Speaker Diarization: Segmenting audio streams and attributing speech to different speakers.
Advanced AI Model Training
Specialized data services for fine-tuning and aligning foundation models, including SFT and RLHF.
- Supervised Fine-Tuning (SFT): Curating high-quality, instruction-based datasets to teach models new skills and behaviors.
- Reinforcement Learning from Human Feedback (RLHF): Generating high-quality human preference data to align language models with complex human values.
- Model Evaluation and Benchmarking: Developing frameworks and datasets to assess model performance, safety, and accuracy.
- Custom Data Pipelines: Building automated workflows for collecting, processing, and annotating data for model training.
